BODY BENCHMARKS

Name: Body Benchmarks Human Metrics Database
Creator: Body Benchmarks

You need to enable JavaScript to run this application.

HDL Cholesterol, 18-29, Male, All

HDL Cholesterol - Health metric data from CDC NHANES 2017-2020

Body Benchmarks Research TeamMPH, MS

Health Metrics Specialists

Dedicated team of health scientists and data analysts specializing in body metrics research and population health data.

About Body Publications

Reviewed by: Health Metrics Team

Comprehensive Guide to HDL Cholesterol, 18-29, Male, All

Whether you're tracking your health or interpreting clinical measurements, this metric benchmarks provide essential context. For 18-29 Male of All background, having demographic-specific reference data matters significantly for accurate interpretation. The population median of 50 serves as a central reference point, though individual optimal values may vary. Explore the complete distribution, understand what influences these measurements, and discover how to apply this knowledge to your health journey.

What is HDL Cholesterol?

A measurement of this metric This health metric, measured in appropriate units, provides valuable information for health assessment and monitoring. Understanding what this metric represents and how it varies across populations helps individuals and healthcare providers make informed decisions.

How is HDL Cholesterol Measured?

The procedure for measuring this metric follows evidence-based protocols designed to maximize accuracy and reproducibility. NHANES measurements adhere to detailed procedural manuals that specify every aspect of the measurement process. From subject preparation to data recording, each step follows standardized procedures that minimize measurement error. Key procedural elements include: appropriate subject positioning, correct equipment use, consistent timing, and accurate recording. When these elements are standardized, this metric measurements provide reliable data for health assessment and comparison.

Distribution & Percentiles

The chart below shows how HDL Cholesterol is distributed across the population. The percentile values help you understand where you fall relative to others in your demographic group.

Insufficient data for visualization

This metric does not have enough statistical parameters for generating a visualization.

Understanding Percentile Distribution

The distribution of this metric values across the population follows a characteristic pattern that reveals important health insights. The central 90% of values fall between 25 (5th percentile) and 75 (95th percentile), defining the typical range for healthy individuals. At the center, the median value of 50 indicates that half the population falls above and half below this point. The interquartile range—40 to 60—encompasses the middle 50% of values, representing the most common range. Understanding where your measurement falls within this distribution provides meaningful context for health assessment.

Percentile Values Breakdown

5th Percentile (P5)

5% of the population falls below this value. This represents the lower range of typical variation.

25th Percentile (P25)

25% of the population falls below this value. This represents the lower-middle range.

50th Percentile (Median)

This is the middle value. 50% of the population falls below and 50% falls above this value.

75th Percentile (P75)

75% of the population falls below this value. This represents the upper-middle range.

95th Percentile (P95)

95% of the population falls below this value. This represents the upper range of typical variation.

Mean (Average)

The arithmetic average of all values. This may differ from the median if the distribution is skewed.

Statistical Summary

Standard Deviation15

Distribution TypeNormal

Population18-29, Male

Demographic Variations in HDL Cholesterol

The intersection of demographic factors creates unique patterns in this metric that require matched reference data for accurate assessment. For Male All individuals aged 18-29, the combination of ethnicity, age, and sex produces a specific profile that differs from other demographic combinations. Using precisely matched reference data provides the most relevant comparison for your individual measurement. This demographic specificity enhances the clinical utility and personal relevance of benchmark comparisons.

Factors Affecting HDL Cholesterol

What determines your this metric? Multiple factors contribute, from inherited genetic traits to daily lifestyle choices. Environmental influences, health conditions, and life stage all play roles in shaping individual values. Recognizing this multifactorial nature supports realistic interpretation and informed health decisions. Some influences offer opportunities for modification while others must simply be understood and accepted.

Health Implications of HDL Cholesterol

this metric values contribute to overall health risk assessment when interpreted alongside other factors. Extreme values—particularly those below the 5th or above the 95th percentile—may indicate increased health risks depending on the specific metric and clinical context. However, being at an extreme doesn't automatically mean poor health; some individuals naturally fall at distribution tails. Risk assessment considers: absolute values, trends over time, family history, lifestyle factors, and co-existing health conditions. Within Blood Lipids, this metric contributes specific risk information that clinicians integrate with broader health assessment. Understanding your this metric as one piece of a larger health puzzle supports informed decision-making.

Clinical Significance

Clinical utility of this metric extends beyond simple comparison to population norms. Healthcare providers consider: how values compare to demographic-matched benchmarks, whether significant changes have occurred, presence of associated symptoms, and relationship to other clinical findings. individual clinical significance depends on broader context. this metric contributes specific information to blood lipids evaluation. This nuanced approach enables meaningful clinical decision-making.

Research Insights

Research on this metric has established robust population benchmarks that inform clinical practice and public health policy. The NHANES program, conducted continuously since the 1960s, provides among the most comprehensive this metric data available. This nationally representative survey combines standardized physical measurements with health interviews, enabling researchers to understand how this metric relates to health outcomes across diverse populations. NHANES data has informed countless research studies, clinical guidelines, and health policies.

Practical Applications

Applying this metric knowledge to real-world health decisions involves several practical considerations. First, obtain accurate measurements under appropriate conditions. Second, compare your values to demographic-matched benchmarks. Third, consider trends over time rather than isolated values. Fourth, discuss findings with healthcare providers who can integrate this metric with your complete health picture. Fifth, if warranted, take evidence-based actions to optimize your this metric through lifestyle modifications or medical interventions.

🇧🇷 Dados de Saúde Regionais: Brasil

✓Dados verificados de fontes oficiais

Os dados antropométricos brasileiros vêm da Pesquisa de Orçamentos Familiares (POF) 2008-2009 do IBGE, com medições diretas de mais de 180.000 pessoas.

O Sistema Único de Saúde (SUS) oferece cobertura universal gratuita com programas de atenção básica e monitoramento de saúde populacional.

Dados oficiais de IBGE / Ministério da Saúde ↗

Nota: Os dados principais são do CDC NHANES (EUA). As estatísticas locais são de pesquisas nacionais oficiais. (2024-01)

📊Data Transparency & Sources

Sources & References

Source Citation

Source:CDC NHANES 2017-2020

Year:2017-2020

Population:18-29 Male (All)

Evidence Level:Level 1 (nationally representative survey)

View Original Source →

Frequently Asked Questions

What's considered a healthy this metric?

Normal this metric encompasses a range of values that varies by demographic group. For individuals aged 18-29, Male, All population, the median value is 50. Values between the 5th and 95th percentiles (25 to 75) represent normal variation. Using demographic-matched benchmarks ensures appropriate comparison.

What does my this metric percentile mean?

Percentiles show where your this metric falls relative to others in your demographic group. At the 50th percentile (50), half the population is above and half below. Between the 25th (40) and 75th (60) percentiles represents the middle half of the distribution—where most healthy values fall. Percentiles at extreme ends (below 5th or above 95th) are less common but not necessarily abnormal. Context matters for interpretation.

Can my this metric change over time?

this metric can change over time due to age-related processes, lifestyle modifications, health conditions, and interventions. Some factors are relatively fixed (like genetics), while others respond to deliberate changes (like exercise or diet). In the 18-29 age range, age-related changes may be occurring. Tracking your this metric over time reveals personal trends that provide valuable health information. Consistent measurement conditions enable meaningful comparison of values over time.

What this metric values indicate potential problems?

Consider discussing your this metric with a healthcare provider if: values fall significantly outside normal range (below 5th or above 95th percentile), you've noticed substantial changes over time, values are associated with symptoms, or you have questions about health implications. Being at a percentile extreme doesn't automatically indicate problems—many healthy individuals naturally fall at distribution tails. Clinical significance depends on context, symptoms, and other health factors. Healthcare providers can offer personalized interpretation.

What explains ethnic variation in this metric?

this metric values differ across ethnic groups due to genetic, environmental, and lifestyle factors. All populations show characteristic patterns that reflect population-specific genetics, dietary traditions, activity patterns, and environmental influences. These differences are normal and expected—not indicators of better or worse health. Using All-specific reference data ensures your comparison reflects meaningful variation rather than expected population differences. This demographic specificity improves the accuracy and relevance of health assessment.

Content Information